The Ultimate Guide to Conversational AI in 2022

AI is a technology that has evolved over time and is becoming more valuable every day. Many businesses now invest in AI.

AI can be used by businesses to improve customer experiences and the work of employees at the company. AI reduces the time required for customers to seek help, especially if it is something that can be quickly sorted out by AI. AI can also be used by businesses to improve customer experience.

The 18.6 Billion USD conversational AI market is predicted to grow by 2026. It is growing rapidly, and more than half of companies believe conversational AI is disrupting their industries.

As you can see conversational AI has become a key part of many businesses customer service and marketing strategies.

It is crucial to understand conversational AI so that you can implement it in your business. Today we will be discussing the definitive guide to conversational AI 2022.

What is Conversational AI?

Conversational AI can be described as an upgraded version of a chatbot. It can send automated messages or have conversations between humans and computers. Although it’s still a chatbot, it can converse with humans in a more human-like manner.

They communicate as if they were human. By understanding the meaning of sentences, and then responding in text that is similar to a human, they can communicate just like humans. These chatbots can be used to interact with customers and make them feel like they are talking to a human.

This makes them feel more valued and personalizes their experience.

Chatbot can also respond faster to smaller issues than a human and may take longer to resolve.

Chatbots: Who created them?

ELIZA was the very first chatbot to be recorded in computer science history in 1994. Joseph Weizenbaum from MIT created it. It was here that “Chatterbox” was first created.

ELIZA used keywords and phrases to recognize the input, then sent a pre-programmed reply back. This means that ELIZA was not very personal and would sometimes respond to the same sentences or phrases.

If you say something about your family like “My father is a fisherman,” ELIZA will reply, “Tell me more about your dad.”

ELIZA can recognize the word “father” in English and will provide an automated answer. It will respond to any word that contains the words “father” and “dad”, regardless of whether it is written.

Please tell me what the differences are between conversational AI (or a traditional chatbot)

Although it is easy to mistake conversational Ai for a chatbot, there are enough differences between them to distinguish them.

Conversational AI is the heart of chatbots, virtual assistants, and everything that makes them tick.

Conversational Artificial Intelligence uses machine-learning to understand and analyze human writing. It can then generate a response that corresponds to what the user wrote.

Chatbots can use conversational artificial intelligence, but there are many other ways. Chatbots are not programmed with AI to decide what answer to give, but they can use pre-determined answers or follow rules.

Conversational AI doesn’t follow a set of rules and responds to the context and intent.

Recent research suggests that the global conversational AI market will surpass 32 billion dollars by 2030, according to a recent study. It is currently being invested by many companies without any end.

What is conversational AI?

Conversational AI is a system that uses multiple structures to send different outputs depending upon the input.

Conversational AI can learn and expand its repertoire of questions by using machine learning. Because the AI can learn from every conversation a user makes with it, and thus, can analyze the context and intent of each user’s responses, so that it can answer new questions.

Although it may seem easy at first, machine learning is far more complex than answering questions or providing answers. It is therefore crucial to have the correct AI structure.

These are the main components of conversational AI’s natural language processing.

Machine Learning (ML). Machine learning is an AI component that relies on algorithms and data sets which are constantly improving and evolving. These algorithms are able to learn from previous messages with people, and determine what a person’s response to certain questions and answers.

Natural Language Processing (NLP). This method of language learning works in conjunction with machine learning. It is currently being used. However, deep learning is just around the corner and most conversational AI will switch over to deep learning to better understand the language.

Analyzing the Received Input. This is where AI scans the text that was sent by the user to determine the context and intent.

Dialogue Management: Once NLP has been completed and the inputs have been analyzed, the AI must reply with a suitable response. Dialogue management allows the AI to decide which answer is most appropriate to send to the user using the previously used processes.

Reinforcement Learning: Finally, both the user’s and AI’s responses are stored. Machine learning then analyzes input and output to determine if they are correct. Machine learning then can compare the answers and determine if the intent of the user and that of the AI. If they do, it can better train to answer similar inputs.

What does conversational AI serve?

Many people have used some type of conversational AI at one time or another. They may not have realized they were speaking to an AI and not a human. Some chatbots can be easily identified, while others are more difficult to identify.

Customer service

Conversational AI has many uses. There are many uses for conversational AI. For instance, if customer service has ever used a messenger to communicate with them on their website, it is likely that they were using a chatbot. This chatbot is frequently used to provide customer service as FAQs can be easily programmed into the chatbot’s responses. It also manages bookings, schedules and cancellations.

IT desk service

Chatbots can be used to assist with IT issues and queries. Chatbots are able to help those who may need simple fixes or solutions, rather than keeping IT staff busy. Chatbots can be used to connect users with a person, even if the problem is not solved.


You can also use conversational AI to promote and sell products. These bots can be used to send targeted audiences with sales or promotions. A well-set up chatbot should be able address the person by name and possibly have some basic information.

These bots can be used to get users to subscribe or direct them down the funnel towards your product page.

Data collection

Many companies forget that conversational AI can also be used to collect data.

Your conversational AI program must be able store the multitude of interactions that occur every day. It should also offer specific analytics on the day’s activities.

Keep all customer calls and messages recorded.

All conversations should be searchable to identify customer issues.

You can track specific keywords that are related to your issues in all calls and messages, and search for customer responses.

Gather essential data such as call times, daily responses and the results of reactions per day.

Examples of conversational AI across industries

Conversational AI can be used in many industries for various purposes. These are three examples of conversational AI that have been used in different industries.


SmarAction is scheduling software that uses conversational AI to understand questions about bookings. We all know it can be more complex than simply giving a date and then booking it.

This AI is able to understand natural language and handle any scheduling problems or requests that users might have.

Watson Assistant

IBM developed Watson Assistant and who better to create a conversational AI that can handle customer transactions?

This AI assistant is able to work in many industries including fashion and healthcare.

It can answer simple questions and execute transactions.

Watson Assistant can reduce handling time by 10% and improve customer satisfaction, according to a study.


Cognigy, an excellent conversational AI tool, allows for efficient customer support 24 hours a days.

Cognigy can be used to improve customer service by optimizing the time it takes for customers with questions to get the answers they need.

This software is used by many airlines. After Covid, airlines were faced with many customer service issues related to refunds and cancellations. Cognigy, an AI program similar to AI, can be used to cancel or refund eligible customers without having contact a customer service representative.

This list contains the top conversational AI tools.


It’s easy to see why conversational AI is slowly taking over certain business sectors. It’s not to be taken lightly that conversational AI isn’t necessary to communicate with a person in real life. However, simple tasks can be performed by conversational AI to speed up the process when humans are too busy to do so.